Project Summary The long-term goal of this proposal is to apply causal inference methods to inform implementation of pre-exposure prophylaxis for HIV prevention (PrEP). PrEP is a proven biomedical intervention that has the potential to dramatically reduce the number of HIV infections globally, but insufficient adherence to PrEP is the biggest barrier to its effectiveness. Widespread implementation of PrEP is required to realize PrEP's full public health potential, and the most recent strategic plans and research priorities of NIH, PEPFAR, NIMH, and the Office of AIDS research all reflect the urgent need for more work in implementation science as it relates to HIV prevention. No single HIV prevention program is ideal for all contexts, and before PrEP is rolled out widely, policy- makers need to assess how PrEP should fit into their own HIV prevention programs. This will require estimating the anticipated public health impact of PrEP in each context, and identifying priority populations for targeted adherence support. Transportability provides a timely solution to these challenges currently facing the PrEP implementation field. Transportability is a novel mathematical framework for predicting the anticipated real-world effectiveness of interventions. The objective of this proposal is to use transportability to inform PrEP implementation by estimating PrEP's real-world effectiveness and identifying priority populations for adherence support. Using data from the iPrEx, iPrEx OLE, and PrEP DemoProjects, Aim 1 will illustrate how transportability can be applied to estimate the effectiveness of a randomized intervention in a distinct target population, and Aim 2 will clarify which characteristics and populations should be prioritized for adherence support. The proposed study will provide valuable and timely insight for PrEP implementation, and will serve as a model for estimating real-world effectiveness of PrEP in other target populations. The interdisciplinary training environment, expert mentorship, and use of cutting edge methods will provide the applicant an opportunity to develop unmatched subject matter, technical, and methodological expertise for her career as a future independent researcher in HIV prevention epidemiology.